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Abstract An ideal tracker which follows the sun both north-south and east-west is designed and constructed. It is suitable for mounting a linear concentrator, focusing parabolic concentrator or photovoltaic array of aperture area 2 m2. The apparatus is built with two axes equational mount and controlled by a microprocessor system. The tracking is carried out by utilizing the astronomical coordinates of the sun. As such the present system gives improved tracking capability over the conventional sensor controlled tracker systems. The performance of the tracking system was studied with photovoltaic array mounted on it and tracking error of less than one degree was achieved. This tracking error can be reduced further by proper software.

The mixing process of hot primary zone gases with secondary air must be rapid and intense for an advanced low NOX gas turbine based on a rich-burn/quick-mix/lean-burn (RQL) combustor. The injection of multiple jets normal into a confined crossflow is a key technology for this combustion concept. Therefore, an experimental investigation of a nonreacting mixing process of jets in a crossflow was conducted. The jets were injected through one stage of opposed rows of circular orifices into a slightly heated crossflow within a rectangular duct with no annular bypass. All geometries were tested with in-line and staggered arrangements of the centerlines of the opposed jets. Using the analogy of heat and mass transfer the temperature distribution was measured, and from that the mixing rate was determined for parametric variation of flow and geometric conditions. In accordance with the application to RQL combustion, emphasis was put on high momentum-flux ratios with high mass flow addition. The mixing process was found to be minimally affected by mainstream Reynolds number and mainstream turbulence, but significantly influenced by the addition of swirl to the mainstream. Correlations based on the experimental data were developed describing best mixing depending as a function of geometric conditions (duct height to hole diameter ratio, relative spacing of adjacent jets) and jet to crossflow momentum-flux ratio.

Both electrical and thermal efficiencies combine in determining and evaluating the performance of a PV/T collector. In this study, two PV/T systems consisting of poly and monocrystalline PV panels were used, which are connected from the bottom by a heat exchanger consisting of a spiral tube through which a nanofluid circulates. In this study, a base fluid, water, and ethylene glycol were used, and iron oxide nanoparticles (nano-Fe2O3) were used as an additive. The mixing was carried out according to the highest specifications adopted by the researchers, and the thermophysical properties of the fluid were carefully examined. The prepared nanofluid properties showed a limited effect of the nanoparticles on the density and viscosity of the resulting fluid. As for the thermal conductivity, it increased by increasing the mass fraction added to reach 140% for the case of adding 2% of nano-Fe2O3. The results of the zeta voltage test showed that the supplied suspensions had high stability. When a mass fraction of 0.5% nano-Fe2O3 was added the zeta potential was 68 mV, while for the case of 2%, it reached 49 mV. Performance tests showed a significant increase in the efficiencies with increased mass flow rate. It was found when analyzing the performance of the two systems for nanofluid flow rates from 0.08 to 0.17 kg/s that there are slight differences between the monocrystalline, and polycrystalline systems operating in the spiral type of exchanger. As for the case of using monocrystalline PV the electrical, thermal, and total PV/T efficiencies with 2% added Fe2O3 ranged between 10% to 13.3%, 43–59%, and 59 to 72%, respectively, compared to a standalone PV system. In the case of using polycrystalline PV, the electrical, thermal, and total PV/T efficiencies ranged from 11% to 13.75%, 40.3% to 63%, and 55.5% to 77.65%, respectively, compared to the standalone PV system. It was found that the PV/T electrical exergy was between 45, and 64 W with thermal exergy ranged from 40 to 166 W, and total exergy from 85 to 280 W, in the case of using a monocrystalline panel. In the case of using polycrystalline, the PV/T electrical, thermal, and total exergy were between 45 and 66 W, 42–172 W, and 85–238 W, respectively. The results showed that both types of PV panels can be used in the harsh weather conditions of the city of Baghdad with acceptable, and efficient productivity.

AbstractNowadays, researchers are focusing on the methods of using recycled industrial/agricultural wastes as raw materials, which are not only economically but also environmentally useful. In the recent years, many scholars have conducted research on the rational use of rice husks (RHs) and found that RHs are rich in inorganic/organic components and used in combination with the certain building materials to produce new green composite building materials. This paper studies the method of using RH processed products and the sodium silicate solution (liquid glass) made from RH ash to produce cheap wood substitute composite materials, which can be improved the insulation performance of the wall greatly. Obtained results are determined by comparing with the properties of standard polymer composite materials such as particleboards, chipboards, and medium‐density fiberboards (MDF). The significance of the work is pointing out by solving the problem of recycling large‐tonnage agricultural waste and reproduce products with the consumer's value.

Abstract This study presents and evaluates the feasibility of a novel hybridization of modified Kalina cycle, reverse osmosis desalination, and low-temperature water electrolysis utilizing geothermal energy to yield power, distilled water, and hydrogen, respectively. The scientific impact of the current work has been improved considering the features of Sabalan flash-binary geothermal wells in Iran as a real model through a case study. In addition to designing a novel setup, the smart use of multi-heat recovery technique, modifying the base cycle, and utilizing a part of generated distilled water to produce hydrogen by the electrolyzer are the other structural originalities, distinguishing the current work from the previous studies. The suggested system is scrutinized via a parametric study and optimized based on a genetic algorithm. The parametric study demonstrated that the highest sensitivity of varying the performance criteria of the whole system is attributed to the change in flash tank pressure. Moreover, the multi-objective optimization led to achieving the exergy efficiency and trigeneration gain output ratio as 51.3% and 1.7 for the system, respectively. Furthermore, the system was able to produce 4795 kW of power, 5.3 kg/h of hydrogen, and 19.9 kg/s of distilled water.

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

Abstract Mitigating the effects of environmental deterioration requires a focus on not just CO2 emissions from energy consumption, but also environmental pollution from industry sectors. To reach this goal, recent studies have extended ecological footprint (EF) analysis to identify the ecological drivers of various key industry sectors. The role of the phosphorus (P) industry on the EF within the environmental Kuznets curve (EKC) framework for China is the emphasis of this study. Autoregressive distributive lag (ARDL) as well as the impulse response function and robustness analysis were used to consider a time from 1985 to 2018. The study verifies the EKC hypothesis for China in both the long and the short run, and indispensable determinants are proposed to be included to assure the model’s fitness and robustness when conducting EF analysis of industry sectors. Energy consumption–based carbon emissions have been verified as the dominant contributor to EF, but P use and urbanization have a significant lagged positive influence on EF in the short run. P exports, in particular, have been highlighted as a critical driver of the EF of China’s P industry. The conducted frequency domain causality test reinforced the above findings and demonstrated bidirectional causality at different frequencies. This work suggests that formulating plausible P export policies to alleviate the conflict between the output of China’s P industry and the environmental sustainability of this industry are necessary. In this context, “multidisciplinary, multidimensional, and practical solutions” are most desirable for sustainable P management.

Avec l'augmentation de la demande d'énergie et les sources d'énergie limitées, le système fonctionne à sa capacité maximale. Par conséquent, la capacité de déterminer la stabilité de la tension avant l'effondrement de la tension a fait l'objet d'une grande attention en raison de la complexité du système d'alimentation. Dans cet article, une prédiction de l'indice de stabilité de la tension (VSI) basée sur le réseau neuronal à fonction de base radiale (RBFNN) pour le réseau Super Grid irakien, 400KV. Des données d'apprentissage ont été obtenues pour divers paramètres de variables de charge à l'aide du flux de charge et de la méthode FVSI conventionnelle. L'entrée les données ont été effectuées en utilisant un test de 135 échantillons avec différentes tensions de bus (V b ), puissances active et réactive de bus (P b , Q b ), angle de charge de bus (δ b ) et FVSI ij. Le modèle RBFNN a quatre entrées représentant le (V b , P b , Q b et δ b ), seize nœuds à la couche cachée et un nœud de sortie représentant FVSI ij ont été utilisés pour évaluer la sécurité en ligne. La méthode proposée a été testée dans l'IEEE 30 et un système pratique. Les résultats de simulation montrent que le le procédé proposé est plus approprié pour l'évaluation de la stabilité de la tension en ligne en termes de détection automatique de la ligne de transmission critique lorsque des charges réelles ou réactives supplémentaires sont ajoutées. Con el aumento de la demanda de energía y las fuentes de alimentación limitadas, el sistema funciona a su máxima capacidad. Por lo tanto, la capacidad de determinar la estabilidad de la tensión antes del colapso de la tensión ha recibido una gran atención debido a la complejidad del sistema de alimentación. En este documento, se ha realizado una predicción del índice de estabilidad de la tensión (VSI) basada en la red neuronal de función de base radial (RBFNN) para la red iraquí Super Grid, 400KV. Se han obtenido datos de aprendizaje para diversas configuraciones de variables de carga utilizando el flujo de carga y el método FVSI convencional. La entrada los datos se realizaron mediante el uso de una prueba de 135 muestras con diferentes voltajes de bus (V b ), potencia activa y reactiva del bus (P b , Q b ), ángulo de carga del bus (δ b ) y FVSI ij. El modelo RBFNN tiene cuatro entradas que representan (V b , P b , Q b y δ b ), dieciséis nodos en la capa oculta y un nodo de salida que representa FVSI ij se han utilizado para evaluar la seguridad en línea. El método propuesto se ha probado en el IEEE 30 y un sistema práctico. En los resultados de la simulación muestran que el método propuesto es más adecuado para la evaluación de la estabilidad de la tensión en línea en términos de detección automática de la línea de transmisión crítica cuando se añaden cargas reales o reactivas adicionales. With the increase in power demand and limited power sources has caused the system to operate at its maximum capacity.Therefore, the ability of determine voltage stability before voltage collapse has received a great attention due to the complexity of power system.In this paper a prediction of voltage stability index (VSI) based on radial basis function neural network (RBFNN) for the Iraqi Super Grid network, 400KV.Learning data has been obtained for various settings of load variables using load flow and conventional FVSI method.The input data was performed by using a 135 samples test with different bus voltage (V b ), Bus active and reactive power (P b , Q b ), bus load angle (δ b ) and FVSI ij .The RBFNN model has four input representing the (V b , P b , Q b and δ b ), sixteen nodes at hidden layer and one output node representing FVSI ij have been used to assess the security on line.The proposed method has been tested in the IEEE 30 and a practical system.In Simulation results show that the proposed method is more suitable for on-line voltage stability assessment in term of automatically detection of critical transmission line when additional real or reactive loads are added. مع زيادة الطلب على الطاقة ومحدودية مصادر الطاقة، تسبب النظام في العمل بأقصى طاقته. لذلك، حظيت قدرة تحديد استقرار الجهد قبل انهيار الجهد باهتمام كبير بسبب تعقيد نظام الطاقة. في هذه الورقة، تم التنبؤ بمؤشر استقرار الجهد (VSI) بناءً على الشبكة العصبية الوظيفية الشعاعية (RBFNN) للشبكة الفائقة العراقية، 400 كيلو فولت. تم الحصول على بيانات التعلم لإعدادات مختلفة من متغيرات الحمل باستخدام تدفق الحمل وطريقة FVSI التقليدية. تم إجراء البيانات باستخدام اختبار 135 عينة بجهد ناقل مختلف (V b )، وناقل نشط وقوة تفاعلية (P b ، Q b )، وزاوية تحميل الناقل (δ b ) و FVSI ij. يحتوي نموذج RBFNN على أربعة مدخلات تمثل (V b ، P b ، Q b و δ b )، وستة عشر عقدة في طبقة مخفية وعقدة خرج واحدة تمثل FVSI ij تم استخدامها لتقييم الأمان على الخط. تم اختبار الطريقة المقترحة في IEEE 30 ونظام عملي. في نتائج المحاكاة تظهر أن الطريقة المقترحة أكثر ملاءمة لتقييم استقرار الجهد عبر الإنترنت من حيث الكشف التلقائي عن خط النقل الحرج عند إضافة أحمال حقيقية أو تفاعلية إضافية.

The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.

In this paper the German congestion management regime is analyzed and future congestion management costs are assessed given a higher share of intermittent renewable generation. In this context, cost-based re-dispatching of power plants and technical flexibility through topology optimization are considered as market-based and technical congestion management methods. To replicate the current market regime in Germany a two-step procedure is chosen consisting of a transactional spot market model and a congestion management model. This uniform pricing model is compared to a nodal pricing regime. The results show that currently congestion can mainly be managed by re-dispatching power plants and optimizing the network topology. However, congestion management costs tend to increase significantly in future years if the developments of transmission as well as generation infrastructure diverge. It is concluded that there is a need for improving the current congestion management regime to achieve an efficient longterm development of the German electricity system.